A novel compressing method of airborne SAR raw data

The storage and transmission of SAR raw data are two basic challenges of high-resolution real-time SAR imaging. To address these problems, a new approach for processing SAR raw data combined with compressed sensing (CS) and Block adaptive tree-structure vector quantization (BATSVQ) is proposed in th...

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Bibliographic Details
Main Authors: Yi-chang Chen, Qun Zhang, Guo-zheng Wang, You-qing Bai, Fu-fei Gu
Format: Conference Proceeding
Language:English
Subjects:
block adaptive tree-structure vector quantization(BATSVQ)
compressed sensing(CS)
compressing rate
Image coding
Image reconstruction
Imaging
Radar imaging
Synthetic aperture radar
synthetic aperture radar data
Vectors
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Summary:The storage and transmission of SAR raw data are two basic challenges of high-resolution real-time SAR imaging. To address these problems, a new approach for processing SAR raw data combined with compressed sensing (CS) and Block adaptive tree-structure vector quantization (BATSVQ) is proposed in this paper. For SAR returned signals, CS is engaged to down-sample the radar echoes in the pulse duration. Then, BATSVQ is employed to diminish encode number of every sample value. The compressed data can be transmitted effectively. In the signal receiver, data reconstruction process contains the two ordinal steps according to BATSVQ algorithm and CS reconstruction. Afterward, the Chirp Scaling imaging algorithm is executed to achieve the final SAR image. The simulation results and analysis validate the effectiveness of the proposed method.
DOI:10.1109/ICSPCC.2013.6663970